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Music Intelligence

CommunityPopular
0xsline
music-intelligence

Run or inspect local music analysis and plan or apply beat-, downbeat-, or section-synced video cuts or photo placements. Use for BGM beat edits, rhythm cuts, 卡点剪辑, musical structure, BPM, mood, genre, or instrument questions.

Overview

Publisher0xsline
RepositoryOpenChatCut
Skill namemusic-intelligence
Stars
1.9K
Forks
277
Bundled files
Instructions only
LicenseAGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by 0xsline on GitHub. Read the source before you install it.

Installation

Install the Music Intelligence AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/0xsline/OpenChatCut.git /tmp/OpenChatCut
mkdir -p .claude/skills
cp -r /tmp/OpenChatCut/src/agent/skills/music-intelligence .claude/skills/music-intelligence
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Music Intelligence in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Music Intelligence on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Music Intelligence is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Music Intelligence

  1. Call analyze_music when the user asks to analyze music or no cache exists. It runs the installed local Beat This + CLAP models, waits for completion, and never downloads models; use force:true only for an explicit reanalysis request.
  2. Call inspect_music when only the existing cache is needed.
  3. Before cutting video, call music_edit_plan and show its bounded cut/target summary. Before placing photos, call music_image_plan and show its bounded placement summary. Prefer timing:auto; choose sparse, medium, or dense from the requested pace.
  4. Only after the plan is accepted, call sync_cuts_to_music or sync_images_to_music with the returned analysisRef. Each tool recomputes the plan, rejects stale analysis, and applies its changes as one undo step.
  5. If required model packs are missing, report the returned install guidance (Settings path + missing pack names), then ask whether to proceed with a detect_beats fallback for pure beat timing (BPM + beat frames only, no CLAP tags/sections/energy), or wait until the user installs the packs and retry analyze_music after installation.
  6. Never request, return, quote, summarize, or place the CLAP embedding in model context. Use tags, sections, confidence, and the opaque analysisRef only.

Preconditions

  • Analysis is opt-in and on-device. The media-pool asset must already have a cache for its current sourceRevision.
  • rhythm-lite supplies Beat This rhythm data; music-semantics-lite supplies CLAP tags and the private similarity vector.
  • An Agent call must never install a pack, download a model, decode media, or start inference. Direct the user to Settings and the media-card analysis action when the cache is unavailable.

Inspect

  • Identify the BGM by itemId, assetId, or an unambiguous name. Prefer the timeline item when the user intends to edit, because returned points are then mapped to timeline frames through the clip trim and playback rate.
  • inspect_music returns BPM, meter, confidence, tags, sections, counts, and bounded point lists. Lists are capped at 48 beats, 24 downbeats, 16 sections, and 12 tags; use a narrower range when truncated is true.
  • Treat analysisRef as opaque. It binds later planning and execution to the exact cached analysis without exposing the 512-value CLAP embedding.

Plan

  • timing:auto chooses section → downbeat → beat for sparse edits, downbeat → beat → section for medium edits, and beat → downbeat → section for dense edits.
  • Density samples every fourth, second, or first candidate for sparse, medium, or dense respectively.
  • Plans are bounded to 96 cut frames and 64 overlapping video targets. Report the returned summary and any cap or locked-target warning before applying.
  • A plan targets video clips that overlap the selected BGM range. It must never include or mutate the BGM item itself.

Photo placement

  • music_image_plan uses explicitly listed image asset ids in their given order, or all image assets in media-pool order when omitted. It cycles that order when the music range has more beat intervals than images.
  • Each placement covers the complete interval from one selected timing point to the next, including the BGM range boundaries, so images are not appended with their source duration or placed at a uniform default length.
  • Image placement is bounded to 96 clips and 64 image assets. sync_images_to_music requires an unlocked, empty target video track for the requested range; choose another track instead of overwriting existing content.

Apply and recover

  • Pass the same itemId, timing, density, range, target ids, and analysisRef to sync_cuts_to_music. Execution recomputes the plan from current state; do not replay an old list of frames.
  • A missing or stale ref means the project or analysis changed. Call inspect_music, then music_edit_plan or music_image_plan, and ask for acceptance again.
  • Locked video tracks are skipped and reported. Never unlock a track implicitly.
  • Successful splits are submitted as one EditorCommands.batch, so the whole rhythm edit is one undo step.
  • Successful photo placements are submitted as one EditorCommands.batch, so the whole sequence is one undo step.

Frequently asked questions

What does the Music Intelligence AI skill do?

Run or inspect local music analysis and plan or apply beat-, downbeat-, or section-synced video cuts or photo placements. Use for BGM beat edits, rhythm cuts, 卡点剪辑, musical structure, BPM, mood, genre, or instrument questions.

Why use Music Intelligence on TypingMind?

Because you install it once and use it with any model. Music Intelligence is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Music Intelligence in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/0xsline/OpenChatCut/tree/main/src/agent/skills/music-intelligence. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Music Intelligence?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Music Intelligence?

As many as you like. As long as a model supports skills, you can use Music Intelligence with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Music Intelligence AI skill free?

Yes. It is published on GitHub by 0xsline under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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